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Hamanasu QwQ V2 RP by Delta-Vector

 »  All LLMs  »  Delta-Vector  »  Hamanasu QwQ V2 RP   URL Share it on

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Base model:delta-vector/hamana... Base model:finetune:delta-vect...   Dataset:mielikki/erebus-87k Dataset:neweden/basket-weaving... Dataset:neweden/bluesky-10k-co... Dataset:neweden/creative writi... Dataset:neweden/deepseekrp-fil... Dataset:neweden/discord-filter... Dataset:neweden/limarp-complex... Dataset:neweden/misc-data-shar... Dataset:neweden/opencai-shareg... Dataset:neweden/orion-asstr-st...   Dataset:neweden/orion-lit Dataset:neweden/rp-logs-v2-exp... Dataset:neweden/storium-prefix... Dataset:pocketdoc/dans-kinomax... Dataset:pocketdoc/dans-persona...   Finetuned   Instruct   Qwen   Qwen2   Region:us   Roleplay   Safetensors   Sharded   Storywriting   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Delta-Vector/Hamanasu-QwQ-V2-RP 

Hamanasu QwQ V2 RP Benchmarks

LLME Score: 0.25254
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Hamanasu QwQ V2 RP (Delta-Vector/Hamanasu-QwQ-V2-RP)

Hamanasu QwQ V2 RP Parameters and Internals

LLM NameHamanasu QwQ V2 RP
Repository 🤗https://huggingface.co/Delta-Vector/Hamanasu-QwQ-V2-RP 
Base Model(s)  Delta-Vector/Hamanasu-QwQ-V1.5-Instruct   Delta-Vector/Hamanasu-QwQ-V1.5-Instruct
Model Size32b
Required VRAM65.8 GB
Updated2025-04-23
MaintainerDelta-Vector
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-14   4.9 GB: 2-of-14   4.9 GB: 3-of-14   4.9 GB: 4-of-14   4.9 GB: 5-of-14   4.9 GB: 6-of-14   4.9 GB: 7-of-14   4.9 GB: 8-of-14   4.9 GB: 9-of-14   4.9 GB: 10-of-14   4.9 GB: 11-of-14   4.9 GB: 12-of-14   4.9 GB: 13-of-14   2.1 GB: 14-of-14   0.0 GB   0.0 GB
Model ArchitectureQwen2ForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.49.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than Delta-Vector/Hamanasu-QwQ-V2-RP.

Rank the Hamanasu QwQ V2 RP Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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